| //===----------------------------------------------------------------------===// |
| // |
| // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions. |
| // See https://llvm.org/LICENSE.txt for license information. |
| // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception |
| // |
| //===----------------------------------------------------------------------===// |
| |
| #ifndef _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H |
| #define _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H |
| |
| #include <__config> |
| #include <__random/exponential_distribution.h> |
| #include <__random/normal_distribution.h> |
| #include <__random/uniform_real_distribution.h> |
| #include <cmath> |
| #include <iosfwd> |
| #include <limits> |
| |
| #if !defined(_LIBCPP_HAS_NO_PRAGMA_SYSTEM_HEADER) |
| #pragma GCC system_header |
| #endif |
| |
| _LIBCPP_PUSH_MACROS |
| #include <__undef_macros> |
| |
| _LIBCPP_BEGIN_NAMESPACE_STD |
| |
| template<class _IntType = int> |
| class _LIBCPP_TEMPLATE_VIS poisson_distribution |
| { |
| public: |
| // types |
| typedef _IntType result_type; |
| |
| class _LIBCPP_TEMPLATE_VIS param_type |
| { |
| double __mean_; |
| double __s_; |
| double __d_; |
| double __l_; |
| double __omega_; |
| double __c0_; |
| double __c1_; |
| double __c2_; |
| double __c3_; |
| double __c_; |
| |
| public: |
| typedef poisson_distribution distribution_type; |
| |
| explicit param_type(double __mean = 1.0); |
| |
| _LIBCPP_INLINE_VISIBILITY |
| double mean() const {return __mean_;} |
| |
| friend _LIBCPP_INLINE_VISIBILITY |
| bool operator==(const param_type& __x, const param_type& __y) |
| {return __x.__mean_ == __y.__mean_;} |
| friend _LIBCPP_INLINE_VISIBILITY |
| bool operator!=(const param_type& __x, const param_type& __y) |
| {return !(__x == __y);} |
| |
| friend class poisson_distribution; |
| }; |
| |
| private: |
| param_type __p_; |
| |
| public: |
| // constructors and reset functions |
| #ifndef _LIBCPP_CXX03_LANG |
| _LIBCPP_INLINE_VISIBILITY |
| poisson_distribution() : poisson_distribution(1.0) {} |
| _LIBCPP_INLINE_VISIBILITY |
| explicit poisson_distribution(double __mean) |
| : __p_(__mean) {} |
| #else |
| _LIBCPP_INLINE_VISIBILITY |
| explicit poisson_distribution(double __mean = 1.0) |
| : __p_(__mean) {} |
| #endif |
| _LIBCPP_INLINE_VISIBILITY |
| explicit poisson_distribution(const param_type& __p) : __p_(__p) {} |
| _LIBCPP_INLINE_VISIBILITY |
| void reset() {} |
| |
| // generating functions |
| template<class _URNG> |
| _LIBCPP_INLINE_VISIBILITY |
| result_type operator()(_URNG& __g) |
| {return (*this)(__g, __p_);} |
| template<class _URNG> result_type operator()(_URNG& __g, const param_type& __p); |
| |
| // property functions |
| _LIBCPP_INLINE_VISIBILITY |
| double mean() const {return __p_.mean();} |
| |
| _LIBCPP_INLINE_VISIBILITY |
| param_type param() const {return __p_;} |
| _LIBCPP_INLINE_VISIBILITY |
| void param(const param_type& __p) {__p_ = __p;} |
| |
| _LIBCPP_INLINE_VISIBILITY |
| result_type min() const {return 0;} |
| _LIBCPP_INLINE_VISIBILITY |
| result_type max() const {return numeric_limits<result_type>::max();} |
| |
| friend _LIBCPP_INLINE_VISIBILITY |
| bool operator==(const poisson_distribution& __x, |
| const poisson_distribution& __y) |
| {return __x.__p_ == __y.__p_;} |
| friend _LIBCPP_INLINE_VISIBILITY |
| bool operator!=(const poisson_distribution& __x, |
| const poisson_distribution& __y) |
| {return !(__x == __y);} |
| }; |
| |
| template<class _IntType> |
| poisson_distribution<_IntType>::param_type::param_type(double __mean) |
| // According to the standard `inf` is a valid input, but it causes the |
| // distribution to hang, so we replace it with the maximum representable |
| // mean. |
| : __mean_(isinf(__mean) ? numeric_limits<double>::max() : __mean) |
| { |
| if (__mean_ < 10) |
| { |
| __s_ = 0; |
| __d_ = 0; |
| __l_ = _VSTD::exp(-__mean_); |
| __omega_ = 0; |
| __c3_ = 0; |
| __c2_ = 0; |
| __c1_ = 0; |
| __c0_ = 0; |
| __c_ = 0; |
| } |
| else |
| { |
| __s_ = _VSTD::sqrt(__mean_); |
| __d_ = 6 * __mean_ * __mean_; |
| __l_ = _VSTD::trunc(__mean_ - 1.1484); |
| __omega_ = .3989423 / __s_; |
| double __b1_ = .4166667E-1 / __mean_; |
| double __b2_ = .3 * __b1_ * __b1_; |
| __c3_ = .1428571 * __b1_ * __b2_; |
| __c2_ = __b2_ - 15. * __c3_; |
| __c1_ = __b1_ - 6. * __b2_ + 45. * __c3_; |
| __c0_ = 1. - __b1_ + 3. * __b2_ - 15. * __c3_; |
| __c_ = .1069 / __mean_; |
| } |
| } |
| |
| template <class _IntType> |
| template<class _URNG> |
| _IntType |
| poisson_distribution<_IntType>::operator()(_URNG& __urng, const param_type& __pr) |
| { |
| double __tx; |
| uniform_real_distribution<double> __urd; |
| if (__pr.__mean_ < 10) |
| { |
| __tx = 0; |
| for (double __p = __urd(__urng); __p > __pr.__l_; ++__tx) |
| __p *= __urd(__urng); |
| } |
| else |
| { |
| double __difmuk; |
| double __g = __pr.__mean_ + __pr.__s_ * normal_distribution<double>()(__urng); |
| double __u; |
| if (__g > 0) |
| { |
| __tx = _VSTD::trunc(__g); |
| if (__tx >= __pr.__l_) |
| return _VSTD::__clamp_to_integral<result_type>(__tx); |
| __difmuk = __pr.__mean_ - __tx; |
| __u = __urd(__urng); |
| if (__pr.__d_ * __u >= __difmuk * __difmuk * __difmuk) |
| return _VSTD::__clamp_to_integral<result_type>(__tx); |
| } |
| exponential_distribution<double> __edist; |
| for (bool __using_exp_dist = false; true; __using_exp_dist = true) |
| { |
| double __e; |
| if (__using_exp_dist || __g <= 0) |
| { |
| double __t; |
| do |
| { |
| __e = __edist(__urng); |
| __u = __urd(__urng); |
| __u += __u - 1; |
| __t = 1.8 + (__u < 0 ? -__e : __e); |
| } while (__t <= -.6744); |
| __tx = _VSTD::trunc(__pr.__mean_ + __pr.__s_ * __t); |
| __difmuk = __pr.__mean_ - __tx; |
| __using_exp_dist = true; |
| } |
| double __px; |
| double __py; |
| if (__tx < 10 && __tx >= 0) |
| { |
| const double __fac[] = {1, 1, 2, 6, 24, 120, 720, 5040, |
| 40320, 362880}; |
| __px = -__pr.__mean_; |
| __py = _VSTD::pow(__pr.__mean_, (double)__tx) / __fac[static_cast<int>(__tx)]; |
| } |
| else |
| { |
| double __del = .8333333E-1 / __tx; |
| __del -= 4.8 * __del * __del * __del; |
| double __v = __difmuk / __tx; |
| if (_VSTD::abs(__v) > 0.25) |
| __px = __tx * _VSTD::log(1 + __v) - __difmuk - __del; |
| else |
| __px = __tx * __v * __v * (((((((.1250060 * __v + -.1384794) * |
| __v + .1421878) * __v + -.1661269) * __v + .2000118) * |
| __v + -.2500068) * __v + .3333333) * __v + -.5) - __del; |
| __py = .3989423 / _VSTD::sqrt(__tx); |
| } |
| double __r = (0.5 - __difmuk) / __pr.__s_; |
| double __r2 = __r * __r; |
| double __fx = -0.5 * __r2; |
| double __fy = __pr.__omega_ * (((__pr.__c3_ * __r2 + __pr.__c2_) * |
| __r2 + __pr.__c1_) * __r2 + __pr.__c0_); |
| if (__using_exp_dist) |
| { |
| if (__pr.__c_ * _VSTD::abs(__u) <= __py * _VSTD::exp(__px + __e) - |
| __fy * _VSTD::exp(__fx + __e)) |
| break; |
| } |
| else |
| { |
| if (__fy - __u * __fy <= __py * _VSTD::exp(__px - __fx)) |
| break; |
| } |
| } |
| } |
| return _VSTD::__clamp_to_integral<result_type>(__tx); |
| } |
| |
| template <class _CharT, class _Traits, class _IntType> |
| basic_ostream<_CharT, _Traits>& |
| operator<<(basic_ostream<_CharT, _Traits>& __os, |
| const poisson_distribution<_IntType>& __x) |
| { |
| __save_flags<_CharT, _Traits> __lx(__os); |
| typedef basic_ostream<_CharT, _Traits> _OStream; |
| __os.flags(_OStream::dec | _OStream::left | _OStream::fixed | |
| _OStream::scientific); |
| return __os << __x.mean(); |
| } |
| |
| template <class _CharT, class _Traits, class _IntType> |
| basic_istream<_CharT, _Traits>& |
| operator>>(basic_istream<_CharT, _Traits>& __is, |
| poisson_distribution<_IntType>& __x) |
| { |
| typedef poisson_distribution<_IntType> _Eng; |
| typedef typename _Eng::param_type param_type; |
| __save_flags<_CharT, _Traits> __lx(__is); |
| typedef basic_istream<_CharT, _Traits> _Istream; |
| __is.flags(_Istream::dec | _Istream::skipws); |
| double __mean; |
| __is >> __mean; |
| if (!__is.fail()) |
| __x.param(param_type(__mean)); |
| return __is; |
| } |
| |
| _LIBCPP_END_NAMESPACE_STD |
| |
| _LIBCPP_POP_MACROS |
| |
| #endif // _LIBCPP___RANDOM_POISSON_DISTRIBUTION_H |
